Senior Associate, Data Science - Consumer Credit Risk Models and Data

Senior Associate, Data Science - Consumer Credit Risk Models and Data Job Description Team Description Have you ever seen the headline in the news “Banks Pass Federal Reserve Stress Tests” and wondered how Capital One determines how much savings (or “capital”) it needs?  Or maybe how we analyze the potential impact of the next recession?  At the heart of these questions are sophisticated econometric loss models that help us understand the ways in which the economy impacts our loan portfolios and guide strategic decision making at the highest levels of Capital One.  In the Consumer Credit Risk Management Models and Data Team, we blend cutting-edge quantitative methods, with a deep understanding of our business, data, and regulatory environment to build and deploy predictive models for losses, account volumes and outstanding balances. These models drive key strategic decisions for loss allowances, stress testing, and capital allocation as well as informing our earnings calls and recession preparedness. If this sounds interesting to you, join us! As a Data Scientist on the deployment & platform side of the team, you’ll be at the forefront helping us to usher in the next wave of disruption by using the latest technology to deploy, optimize and modernize model pipelines and execution platforms that enable machine learning models to provide powerful insights about our portfolio and growth opportunities through new data sources. You will partner with best-in-class data scientists, analysts, and engineers to innovate solutions that directly impact the company’s bottom line in a meaningful way. You will do it all in a collaborative environment that values your insight, encourages you to take on new responsibilities, promotes continuous learning, and rewards innovation. Role Description In this role, you will: - Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love - Leverage a broad stack of technologies — Python, Conda, AWS, Spark, and more — to reveal the insights hidden within huge volumes of data - Optimize and deploy machine learning models through all phases of development, from design through training, evaluation, validation, and implementation - Flex your interpersonal skills to translate the complexity of your work into tangible business goals The Ideal Candidate is: - Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it’s about making the right decision for our customers. - Technical. You’re comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms. - A data guru. “Big data” doesn’t faze you. You have the skills to retrieve, combine, and analyze data from a variety of sources and structures. You know understanding the data is often the key to great data science. - Statistically-minded. You’ve built models, validated them, and back tested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, sentiment analysis, time series, and deep learning. Basic Qualifications: - Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date: - A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 2 years of experience performing data analytics - A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration Preferred Qualifications:  - Master’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics), or PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) - Experience working with AWS - At least 2 years’ experience in Python, Scala, or R - At least 2 years’ experience with machine learning - At least 2 years’ experience with SQL  Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $135,600 - $154,800 for Sr Assoc, Data Science Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.